Mapping innovation in energy startups: A data fusion journey with OpenCorporates and Semantic Scholar

Today’s energy sector is evolving fast. With thousands of new companies emerging each year, keeping track of innovative startups is both a challenge and an opportunity. So how can investors, policymakers, and researchers quickly identify the most promising ventures, especially those with deep scientific expertise? In this post, I’ll walk through the methodology, share some key findings, and explain how this approach opens new doors for data-driven innovation analysis.

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Case study: How Datastruct replaced manual checks with reliable entity intelligence

Manual Secretary of State (SOS) research was slowing teams down, creating data gaps, and increasing compliance risk. Relying on manual, state-by-state desktop research and ad hoc tracking was time-consuming, inconsistent, and difficult to scale, leading to outdated information and operational inefficiencies. This was why it was critical to automate access to accurate, real-time entity information as the business scaled and recovery volumes grew.

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Delaware is “losing incorporations”? Our data shows a different story

Delaware’s incorporations are still growing in absolute terms. Our data shows Delaware’s total recorded companies rising from 5.02m (Nov 2023) to 5.30m (Nov 2024) to 5.62m (Nov 2025), a ~10% increase over two years. The real change is in where new, small entities (especially LLCs) are being formed. Our December 2024 blog series documents that Wyoming overtook Delaware in new incorporations on a per‑capita basis, powered by a nationwide explosion in LLCs. High‑profile “DEXIT” reincorporations are happening, but they don’t equal an overall collapse. After court‑driven flashpoints, some large companies announced moves (e.g., Tesla and SpaceX), a visible but numerically limited subset of total formations.

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15 years of corporate transparency: The ultimate resource list

Fifteen years ago, Chris Taggart founded OpenCorporates with a simple mission: to make legal-entity data transparent and reliable. Today, that mission is more critical than ever. We've built the foundation for the first step of any transaction; verifying a legitimate business from its primary source, such as Secretaries of State and Companies House. OpenCorporates was an early innovator in this space, establishing itself as the most trusted source for legal-entity data, anchored in our seven Legal-Entity Data Principles. This commitment to provenance and quality is what sets our data apart.

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When auditors ask “where did this data come from?” Can you answer?

Provenance means the ability to trace every data point back to its official source with timestamps. This capability addresses the trust gap in business data by providing clear lineage for compliance decisions. This article examines why data transparency has become essential for compliance operations, how leading organizations implement it, and what it means for business data management.

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OpenCorporates brings world’s largest open company database to Money20/20 USA

OpenCorporates, the world’s largest open database of legal entity data, will make its debut at Money20/20 USA (Oct 26–29, 2025, Las Vegas). The company will showcase how standardised, transparent, official legal entity data empowers fintechs, RegTechs, and financial institutions to meet regulatory demands, enhance KYC/KYB, and combat financial crime. Visit OpenCorporates at Booth #19703 for live demos and exclusive insights.

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The tequila heist that exposed supply chain fraud – and the fake companies behind it

The Santo Tequila case is a classic example of double brokering - when one freight company passes a shipment to another, and then another. At some point in the chain, a non-existent “carrier” steps in. These so-called phantom carriers look credible: they have names like Acme Logistics LLC, registered phone numbers, even government-issued identification numbers. But behind them, there’s often no legal entity, no employees, and sometimes not even a real address. They win contracts, move goods - and then disappear.

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Making sense of risk with legal-entity knowledge graphs

Companies, banks, and regulators can no longer rely on a single dataset or a single rulebook. They need to bring multiple pieces of information together to understand risk and make informed decisions. This is where legal-entity knowledge graphs (LE-KGs) come in. They act as the “map” of companies and their connections, showing ownership, control, and risk.

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What you need to know before sourcing data directly from US state registries

Collecting, cleaning, and maintaining company data directly from 50 separate US state registries (plus DC and territories) is possible - but only with significant, ongoing expense in money, time, and specialist effort. Variation across states in data availability, formats, fee models, and cadence - paired with legal/licensing friction - turns “do‑it‑yourself” into a long, laborious program rather than a one‑off project. 

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